Update app.py

app.py

@@ -34,7 +34,12 @@ if len(data) > 0:
     
     # Add derived features for better recommendations
     if 'positive_ratings' in data.columns and 'negative_ratings' in data.columns:
+        data['positive_ratings'] = pd.to_numeric(data['positive_ratings'], errors='coerce')
+        data['negative_ratings'] = pd.to_numeric(data['negative_ratings'], errors='coerce')
+        data.dropna(subset=['positive_ratings', 'negative_ratings'], inplace=True)
+
         data['rating_ratio'] = data['positive_ratings'] / (data['positive_ratings'] + data['negative_ratings'] + 1)
+
     else:
         data['rating_ratio'] = 0.5  # Default neutral rating